Chapter II. Prevention and Treatment

Rev Diabet Stud, 2015, 12(3-4):351-362 DOI 10.1900/RDS.2015.12.351

Type 2 Diabetes Prevention: Implications of Hemoglobin A1c Genetics

Aaron Leong1,2, James B. Meigs1,2

1Massachusetts General Hospital, General Medicine Division, Boston, MA, USA
2Harvard Medical School, Boston, MA, USA
Address correspondence to: Aaron Leong, e-mail:


Hemoglobin A1c (HbA1c) is a biomarker used for population-level screening of type 2 diabetes (T2D) and risk stratification. Large-scale, genome-wide association studies have identified multiple genomic loci influencing HbA1c. We discuss the challenges of classifying these genomic loci as influencing HbA1c through glycemic or nonglycemic pathways, based on their probable biology and pleiotropic associations with erythrocyte traits. We show that putative nonglycemic genetic variants have a measurable, albeit small, impact on the classification of T2D status by HbA1c in white and Asian populations. Accounting for their effect on HbA1c may be relevant when screening populations with higher frequencies of nonglycemic HbA1c-altering alleles. As carriers of such HbA1c-altering alleles have HbA1c levels that may not accurately reflect overall glycemia, we describe how accounting for genotype may improve the performance of HbA1c in T2D prediction models and risk stratification, allowing for lifestyle intervention strategies to be directed towards those who are truly at elevated risk for developing T2D. In a Mendelian randomization framework, genetic variants can be used as instrumental variables to estimate causal relationships between HbA1c and T2D-related complications. This approach may help to support or refute HbA1c as an appropriate biomarker for long-term health outcomes in the general population.

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Rev Diabet Stud, 2015, 12(3-4):363-376 DOI 10.1900/RDS.2015.12.363

Pharmacogenetics: Implications for Modern Type 2 Diabetes Therapy

Harald Staiger1,2,3,4, Elke Schaeffeler1,5,6, Matthias Schwab1,5,6, Hans-Ulrich Häring1,2,3,4

1Interfaculty Centre for Pharmacogenomics and Pharma Research at the University of Tübingen, Tübingen, Germany
2Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, University Hospital Tübingen, Tübingen, Germany
3Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Centre Munich at the University of Tübingen, Tübingen, Germany
4German Centre for Diabetes Research (DZD), Tübingen, Germany
5Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
6Department of Clinical Pharmacology, University Hospital Tübingen, Tübingen, Germany
Address correspondence to: Harald Staiger, Internal Medicine IV, University Hospital Tübingen, Otfried-Müller-Str. 10, 72076 Tübingen, Germany; e-mail:


Many clinical treatment studies have reported remarkable interindividual variability in the response to pharmaceutical drugs, and uncovered the existence of inadequate treatment response, non-response, and even adverse drug reactions. Pharmacogenetics addresses the impact of genetic variants on treatment outcome including side-effects. In recent years, it has also entered the field of clinical diabetes research. In modern type 2 diabetes therapy, metformin is established as first-line drug. The latest pharmaceutical developments, including incretin mimetics, dipeptidyl peptidase 4 inhibitors (gliptins), and sodium/glucose cotransporter 2 inhibitors (gliflozins), are currently experiencing a marked increase in clinical use, while the prescriptions of α-glucosidase inhibitors, sulfonylureas, meglitinides (glinides), and thiazolidinediones (glitazones) are declining, predominantly because of reported side-effects. This review summarizes the current knowledge about gene-drug interactions observed in therapy studies with the above drugs. We report drug interactions with candidate genes involved in the pharmacokinetics (e.g., drug transporters) and pharmacodynamics (drug targets and downstream signaling steps) of the drugs, with known type 2 diabetes risk genes and previously unknown genes derived from hypothesis-free approaches such as genome-wide association studies. Moreover, some new and promising candidate genes for future pharmacogenetic assessment are highlighted. Finally, we critically appraise the current state of type 2 diabetes pharmacogenetics in the light of its impact on therapeutic decisions, and we refer to major problems, and make suggestions for future efforts in this field to help improve the clinical relevance of the results, and to establish genetically determined treatment failure.

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